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Sex Differences in Osteoarthritis of the Knee

2012· article· en· W4240037173 on OpenAlexaff
Barbara D. Boyan, Laura L. Tosi, Richard D. Coutts, Roger M. Enoka, David A. Hart, Daniel P. Nicolella, Karen J. Berkley, Kathleen A. Sluka, K. Kwoh, Mary I. O’Connor, Wendy M. Kohrt

Bibliographic record

VenueJournal of the American Academy of Orthopaedic Surgeons · 2012
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineOsteoarthritisIncidence (geometry)DiseaseGerontologyPopulationPhysical therapyQuality of life (healthcare)Ethnic groupDemographyInternal medicineAlternative medicinePathologyEnvironmental health

Abstract

fetched live from OpenAlex

Osteoarthritis (OA) is a leading cause of disability in the United States. It is the most common form of arthritis and afflicts 13.9% of adults aged ≥25 years and 33.6% (12.4 million) of those aged >65 years—an estimated 26.9 million persons in the United States.1 Studies sponsored by the Centers for Disease Control and Prevention and the National Institutes of Health have identified differences in the incidence and severity of OA between men and women, as well as between racial and ethnic groups.2,3 The burden of OA is highest among women and African-Americans, who disproportionately develop knee and hand but not hip OA. The disproportionate number of women in the aging US population is of clinical concern because of the more severe knee OA and its impact on quality of life and independence. Based on these factors, there is a need for research focused on the effect sex differences have in the development and progression of OA as well as the impact on prevention and treatment strategies. However, most studies on the mechanisms underlying OA have not taken sex differences into account, whether in vitro cell culture or animal models were used. Although little is known about the mechanisms that contribute to disparities between men and women in disease incidence and severity, they likely involve mechanical and molecular events in the affected joint. Diagnosis of knee OA is based on evidence of joint pain and/or reduced space between articulating bone surfaces as a result of thinning of the opposing articular cartilages. However, multiple tissues that compose the knee joint appear to be compromised by the disease, including subchondral bone, articular cartilage, the meniscus, the anterior cruciate ligament, the synovium, and synovial fluid. A change in any of these tissues can influence the distribution of load across the joint, with corresponding adaptations in the other tissues and, ultimately, the cartilages. Such pathophysiologic changes may exacerbate age-related physiologic changes in joint function attributable to genetic characteristics, age, sex, and health status, leading to greater cartilage damage. To understand the expression of knee OA in males and females, it is important to view the knee as an organ rather than focusing only on the articular cartilage. Knee tissues are modulated by sex hormones during tissue development and throughout the life cycle in both males and females. Although menopause is associated with an increase in OA severity in women, systemic estrogen alone cannot explain the observed sex differences. Recent data, for example, show that sex-specific variations in the responses of chondrocytes to sex steroids are the result of differences in receptor number as well as mechanisms of hormone action.4 In addition to increased prevalence of knee OA, women often have greater pain and more substantial reduction in function and quality of life than do men.5 OA pain can be related to the sensory information that emerges from the knee joint. The pain does not always match the degree of injury, however, and can continue even after total joint arthroplasty. The neural and other mechanisms underlying these differences in pain between men and women with knee OA are unknown. By improving our understanding of the mechanisms responsible for sex differences in the perception of pain in OA, more effective and, possibly, sex-specific treatment strategies will emerge. Although the adaptations that accompany advancing age may be a major factor in its etiology in older patients, early-onset OA is becoming more common. Women with physically active lifestyles, such as athletes and workers in occupations that involve exposure to traumatic injury or to mechanical stress, are more subject to early onset OA. Anterior cruciate ligament injuries are particularly problematic in 16- to 20-year-old females. Approximately 50% of these young women will progress to OA in 10 to 15 years.6,7 The prevalence of obesity in children and young adults is escalating, and the impact of increased mechanical stress on the knee during bone growth and development is not yet fully understood. In addition, the role of sex differences, particularly hormonal regulation, and its influence on the onset and progression of OA is not yet known. In summary, epidemiologic studies have established that sex differences exist in the incidence and severity of knee OA. Therapeutic approaches to the management of OA, particularly regenerative medicine strategies, have not yet taken these sex differences into consideration. Effective interventions, however, will require a better understanding of the mechanisms involved in the disease and its differential expression in men and women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.022
GPT teacher head0.274
Teacher spread0.252 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations24
Published2012
Admission routes1
Has abstractyes

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